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- W2127596543 abstract "Due to the high computational cost associated with calculation of optimal control policies for a family of Markov chains, sub-optimal policy generation approaches are often required for development of intervention strategies in systems medicine. In this paper, a new infinite-horizon suboptimal policy generation algorithm using a sequential-selection approach with efficient re-calculation of steady-state distributions is presented and compared against brute-force and other sub-optimal algorithms. Our results show that for a system represented by a family of Markov chains, the presented approach is able to generate robust stationary control policies with superior expected behavior in a computationally inexpensive manner." @default.
- W2127596543 created "2016-06-24" @default.
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- W2127596543 date "2012-12-01" @default.
- W2127596543 modified "2023-09-24" @default.
- W2127596543 title "GENERATION OF STATIONARY CONTROL POLICIES WITH BEST EXPECTED PERFORMANCE FOR A FAMILY OF MARKOV CHAINS" @default.
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- W2127596543 doi "https://doi.org/10.1142/s0218339012400050" @default.
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